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Works276 from public data
- Image and Video Compression With Neural Networks: A Review459
The evolution and development of neural network-based compression methodologies are introduced for images and video respectively and the joint compression on semantic and visual information is tentatively explored to formulate high efficiency signal representation structure for both human vision and machine vision.
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- Diffusion-Based 3D Human Pose Estimation with Multi-Hypothesis Aggregation180
A novel Diffusion-based 3D Pose estimation method with Joint-wise reProjection-based Multi-hypothesis Aggregation (JPMA) proposed for probabilistic 3D human pose estimation and to assemble multiple hypotheses generated by D3DP into a single 3D pose for practical use.
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- NTIRE 2024 Challenge on Image Super-Resolution (×4): Methods and Results83
This paper reviews the NTIRE 2024 challenge on image super-resolution (×4), highlighting the solutions proposed and the outcomes obtained, and offers a comprehensive overview of current trends in this field.
- Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-Modal Structured Representations78
This paper presents an end-to-end framework Structure-CLIP, which integrates Scene Graph Knowledge (SGK) to enhance multi-modal structured representations and uses scene graphs to guide the construction of semantic negative examples, which results in an increased emphasis on learning structured representations.
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- Towards Analysis-Friendly Face Representation With Scalable Feature and Texture Compression77
This work investigates the integration of feature and texture compression and shows that a universal and collaborative visual information representation can be achieved in a hierarchical way in a scalable coding framework.
- STRPM: A Spatiotemporal Residual Predictive Model for High-Resolution Video Prediction75
A Spatiotemporal Residual Predictive Model (STRPM) which can supervise the spatial encoder and temporal encoder to extract different features in the spatial domain and the temporal domain, respectively and is trained using generative adversarial networks with a learned perceptual loss to improve the perceptual quality of the predictions.
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- No-reference quality assessment of deblocked images75
Experimental results conducted on the DBID database demonstrate that the proposed metric is effective in evaluating the quality of deblocked images, and it significantly outperforms the existing metrics.
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- Predictive Generalized Graph Fourier Transform for Attribute Compression of Dynamic Point Clouds65
This work proposes a complete compression framework for attributes of 3D dynamic point clouds, focusing on optimal inter-coding and refined motion estimation via efficient registration prior to inter-prediction, which searches the temporal correspondence between adjacent frames of irregular point clouds.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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